Research on Impact Resistance of Aluminum Alloy New Rotating Thin-Walled Structures.

Honeycomb structures are widely used in the field of impact resistance and are constantly being developed and updated. In this paper, the design of three new aluminum alloy rotating thin-walled structures (NRTS) are examined. These structures combine common concave structures and rotating, rigid-body structures. The purpose of this study is to solve the problem of the poor energy absorption capacity of rotating, rigid-body structure due to small deformation and to provide a reference for honeycomb mechanism designs. The Young's modulus, the critical velocity, and the platform stress of the NRTS structure are derived from theoretical analysis. The dynamic response of the NRTS structure at different impact velocities is investigated using finite element simulation software. The results show that the rotating, thin-walled recessed honeycomb (RTRH) increases the plateau stress by 124% and 51% as compared to rotating, thin-walled square tubes (RTSTs) and the re-entrant hexagonal structure (RH), respectively; the rotating, thin-walled quadruple-arc honeycomb structure (RTQH) increases the SEA by 21% and 20% as compared to the RTST and RH, respectively; and the rotating thin-walled double-arc honeycomb structure (RTDH) increases the CEF by 54% and 51% as compared to the RTST and RH, respectively. During the study, it was demonstrated that NTRS also exhibits good energy absorption capacity. Then, the effect of rotation angle on the energy absorption performance was analyzed. The cell and wall thickness of the NTRS structure were optimized according to the gradient theory. It was proved that the gradient optimized structure has better energy absorption performance as compared to the uniform structure.

[Expression and Clinical Significance of Serum MiR-370 and MiR-203 in Patients with Acute Myeloid Leukemia].

OBJECTIVE: To investigate the expression of microRNA-370 (miR-370) and microRNA-203 (miR-203) in the serum of patients with acute myeloid leukemia(AML), and to analyze its clinical diagnosis and prognostic significance. METHODS: 57 patients with acute myeloid leukemia were enrolled as experimental group, and 21 healthy people were enrolled as control group. The fasting venous blood of the personal in the two groups were collected. The expression of miR-370 and miR-203 of the personal in each groups were detected by real-time fluorescent quantitative PCR. The receiver operating characteristic (ROC) curve was plotted to detected the diagnostic values of serum miR-370, miR-203, and the Kaplan-Meier method was used to estimate the relationship between expression and overall survival of the patients. RESULTS: Compared with healthy controls, serum miR-370 expression was significantly decreased in AML patients(P<0.05), and serum miR-203 expression was also significantly decreased (P<0.05). ROC curve analysis showed that the expression of serum miR-370 and miR-203 could be used to distinguish acute myeloid leukemia and healthy people. The area under the ROC curve of miR-370 was 0.909, and the sensitivity and specificity were 91.46% and 100.00%, respectively. The area under the ROC curve of miR-203 was 0.895, and the sensitivity and specificity were 83.45% and 89.71%, respectively. Serum levels of miR-370 and miR-203 were closely related to overall survival in AML patients. CONCLUSION: The expression of miR-370 and miR-203 is decreased in the serum of patients with AML and may be a new markers for the diagnosis and prognosis of AML.

Predicting pathogenic genes for primary myelofibrosis based on a system­network approach.

The aim of the present study was to predict pathogenic genes for primary myelofibrosis (PMF) using a system­network approach by combining protein­protein interaction (PPI) network and gene expression data with known pathogenic genes. PMF gene expression profiles, known pathogenic genes and protein­protein interactions were obtained. Using these data, differentially expressed genes (DEGs) were identified between PMF and normal conditions using significance analysis of microarrays, and seed genes were determined based on the intersection of known pathogenic genes and the PMF gene expression profile. A new network was constructed using the seed genes and their adjacent DEGs within the PPI network. Subsequently, a pathogenic network was extracted from the new network, and contained genes that interacted with at least two seed genes, and the candidate pathogenic genes were predicted based on the cohesion with seed genes. Cluster analysis was performed to mine the pathogenic modules from the pathogenic network, and functional analysis was performed to identify the putative biological processes of the candidate pathogenic genes. Results from the present study identified 845 DEGs between PMF and normal conditions, and 45 seed genes in PMF were screened. Subsequently, a pathogenic network comprising 103 nodes and 265 interactions was constructed, and 4 pathogenic modules (modules A­D) were mined from the pathogenic network. There were nine candidate pathogenic genes contained within Module A and four potential pathogenic genes, including E1A­binding protein p300, RAS­like proto­oncogene A, von Willebrand factor and RAF­1 proto­oncogene, serine/threonine kinase, were identified that may be involved in the same biological process with the seed genes. This study predicted 10 candidate pathogenic genes and several signaling pathways that may be related to the pathogenesis of PMF using a system­network approach. These predictions may shed light on the PMF pathogenesis and may provide guidelines for future experimental verification.